Characterization of the Communication Patterns of Scientific Applications on Blue Gene/P

This paper examines the communication characteristics of a collection of scientific applications selected from the LLNL's Sequoia suite of benchmarks and the ANL's workload. By using an instrumentation library built on top of MPI we collect and characterize the applications's messaging behavior: the type of communication patterns and primitives used, the amount of time spent for communication, the message sizes, the total amount of data exchanged, and the impact of collective primitives, through communication matrices we visualize the actual communication patterns to highlight symmetries and other relevant peculiarities. Our analysis exposes several similarities between the applications -- namely the utilization of common low-dimensional stencils, and the use of a small set of collective primitives, in particular all-reduces with small vectors. Overall, our study provides a better understanding of the communication characteristics of several important scientific applications and benchmarks.